ReadMe.txt

%% PSO-LPQ Image Features - Created in 22 Jan 2022 by Seyed Muhammad Hossein Mousavi
% This code extracts Local Phase Quantization (LPQ) features out of 100
% samples of images in 10 classes. LPQ features are in the family of frequency based features.
% Then desired number of PSO features
% will be selected out of extracted LPQ features which have highest
% impact. Actually, you can select n strongest features. Results show,
% however number of selected features goes down, but recognition accuracy
% is almost intact. 'nf' is number of selected features by PSO. Images are
% stores in 'data' folder. 
% ------------------------------------------------ 
% Feel free to contact me if you find any problem using the code: 
% Author: SeyedMuhammadHosseinMousavi
% My Email: mosavi.a.i.buali@gmail.com 
% My Google Scholar: https://scholar.google.com/citations?user=PtvQvAQAAAAJ&hl=en 
% My GitHub: https://github.com/SeyedMuhammadHosseinMousavi?tab=repositories 
% My ORCID: https://orcid.org/0000-0001-6906-2152 
% My Scopus: https://www.scopus.com/authid/detail.uri?authorId=57193122985 
% My MathWorks: https://www.mathworks.com/matlabcentral/profile/authors/9763916#
% my RG: https://www.researchgate.net/profile/Seyed-Mousavi-17
% ------------------------------------------------ 
% Hope it help you, enjoy the code and wish me luck :)